Ontology for autonomous robotics

Creating a standard for knowledge representation and reasoning in autonomous robotics is an urgent task if we consider recent advances in robotics as well as predictions about the insertion of robots in human daily life. Indeed, this will impact the way information is exchanged between multiple robots or between robots and humans and how they can all understand it without ambiguity. Indeed, Human Robot Interaction (HRI) represents the interaction of at least two cognition models (Human and Robot). Such interaction informs task composition, task assignment, communication, cooperation and coordination in a dynamic environment, requiring a flexible representation. Hence, this paper presents the IEEE RAS Autonomous Robotics (AuR) Study Group, which is a spin-off of the IEEE Ontologies for Robotics and Automation (ORA) Working Group, and its ongoing work to develop the first IEEE-RAS ontology standard for autonomous robotics. In particular, this paper reports on the current version of the ontology for autonomous robotics as well as on its first implementation successfully validated for a human-robot interaction scenario, demonstrating the developed ontology’s strengths which include semantic interoperability and capability to relate ontologies from different fields for knowledge sharing and interactions.info:eu-repo/semantics/publishedVersio

CEG 499-01: WWW Autonomous Robotics

WWW Autonomous Robotics is a computer engineering practicum offered entirely via the Internet. The course adopts a low threshold, no ceiling philosophy. This means that the course is designed to be inclusive of students with limited formal training while still providing significant challenges for those with greater preparation and/or motivation. Students will be required to create control programs for a mobile autonomous robot. In each course unit, the problems posed will become increasingly more challenging. Coaching, advise, and instruction are done online via chat interfaces. Student code is tested first in a simulator that we provide and then on a real robot whose activity can be monitored remotely via a web cam

Autonomous Robotics in the AEC practice

In recent years, technical development in robotics has been enhanced by leaps forward in artificial intelligence and machine learning (ML). Today’s robots learn and optimize their motion, are remotely connected and ready for deployment, and can transfer learned models and behaviors between industries or applications.1 This paradigm shift and step change in available autonomy necessitates rethinking how robotics may impact the AEC industry. Until now, contractors and fabricators have mainly used robots to replace humans in the narrow opportunity presented by “Dull, Dirty, and Dangerous” tasks (the 3Ds)—repeated millions of times with little variability. However, AEC professionals are starting to explore robots’ ability to perform tasks that are “Specific, Sustainable, and Scalable” (the 3Ss). Robots complete specific tasks by producing one-off designs and sustainable tasks as they render viable reuse as well as material and waste reduction. Yet they maintain scalability by being able to effortlessly multiply into the hundreds or even millions. They are “smart” enough to work alongside humans, rather than replace them

Task-level robot programming: Integral part of evolution from teleoperation to autonomy

An explanation is presented of task-level robot programming and of how it differs from the usual interpretation of task planning for robotics. Most importantly, it is argued that the physical and mathematical basis of task-level robot programming provides inherently greater reliability than efforts to apply better known concepts from artificial intelligence (AI) to autonomous robotics. Finally, an architecture is presented that allows the integration of task-level robot programming within an evolutionary, redundant, and multi-modal framework that spans teleoperation to autonomy

Modular Autonomous Robotics Platform for Educational Use

Robotics is a field that continues to grow as robots become common in environments as varied as households and the battlefield. This paper presents a low cost robotics development platform using commercial off-the-shelf parts for educational and academic use. It is a direct response to the high cost and limited functionality of existing platforms. A navigation and obstacle-avoidance Fuzzy Controller is provided to accelerate the typical development process for a mobile robot. The fundamental aim is to facilitate future robotics projects by producing an inexpensive, modular and highly accessible platform that improves upon existing commercial offerings

An integrated system for autonomous robotics manipulation

We describe the software components of a robotics system designed to autonomously grasp objects and perform dexterous manipulation tasks with only high-level supervision. The system is centered on the tight integration of several core functionalities, including perception, planning and control, with the logical structuring of tasks driven by a Behavior Tree architecture. The advantage of the implementation is to reduce the execution time while integrating advanced algorithms for autonomous manipulation. We describe our approach to 3-D perception, real-time planning, force compliant motions, and audio processing. Performance results for object grasping and complex manipulation tasks of in-house tests and of an independent evaluation team are presented

Teaching humanoid robotics by means of human teleoperation through RGB-D sensors

This paper presents a graduate course project on humanoid robotics offered by the University of Padova. The target is to safely lift an object by teleoperating a small humanoid. Students have to map human limbs into robot joints, guarantee the robot stability during the motion, and teleoperate the robot to perform the correct movement. We introduce the following innovative aspects with respect to classical robotic classes: i) the use of humanoid robots as teaching tools; ii) the simplification of the stable locomotion problem by exploiting the potential of teleoperation; iii) the adoption of a Project-Based Learning constructivist approach as teaching methodology. The learning objectives of both course and project are introduced and compared with the students\u2019 background. Design and constraints students have to deal with are reported, together with the amount of time they and their instructors dedicated to solve tasks. A set of evaluation results are provided in order to validate the authors\u2019 purpose, including the students\u2019 personal feedback. A discussion about possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels